Ask HN: Who wants to be hired? (November 2025)
51–60 of 536 posts
Re: Ask HN: Who wants to be hired? (November 2025)
#52Remote: Preferred
Willing to relocate: Depends on the role. I would prefer to stay in the PNW if possible.
Technologies:
* Languages: Python (proficient), Bash (proficient)
* Libraries: Pytorch, Tensorflow, and all the usual suspects (pandas/numpy/scipy/etc.)
* DevOps: Kubernetes, Ansible, Docker, Zabbix, DNS (TinyDNS/bind), Harvester, Netbox, KeaDHCP, CI/CD
* Infra: Hetzner, AWS, Colo/On Prem.
* HPC: SLURM, Ceph
* Linux systems (Rocky, Debian, Arch)
* Biophysical: GROMACS, OpenMM, FoldX, PyRosetta
Résumé/CV: https://jbarnes.dev/resumeEmail: jonathan [at] jbarnes.dev
LinkedIn: https://www.linkedin.com/in/barnesjonathane/
Hi, I'm Jonathan. I’m currently doing DevOps work for an open source project and operate a small web hosting company. My skill set is focused on the DevOps side, with a bit of general dev experience, primarily with Python. On the side I also host my own infrastructure as a hobby, from the hardware to the nameservers and everything in between.
I'm a strong communicator, having collaborated across disciplines and presented work for both technical and non-technical audiences. Having worked at startups before, I’m comfortable wearing many hats (and enjoy the variety). I'm self-motivated, a strong problem solver, and love to dig into new complex problems and learn new tools.
Re: Ask HN: Who wants to be hired? (November 2025)
#53Remote: Yes (EU/US time zones). Willing to relocate: Yes
Technologies: Rust, Python, PyTorch, NumPy/Pandas, Flask, Django, SQL, Docker; machine learning, deep learning
Industries/domain expertise: PhD in mathematics (statistical methods/modeling, topological data analysis, representation theory); master's theses in finance and neuroscience; applications of machine learning/deep learning to banking/finance for risk evaluation and fraud prediction; LLMs and agentic frameworks (tools, planning, evaluation)
Rust focus: async services (Tokio, Axum/Actix), data/compute (Polars/Arrow); production systems and performance-critical pipelines
Résumé/CV: available on request
Systems-oriented ML/LLM engineer using Python/PyTorch and Rust for low-latency/high throughput services. I've worked across domains (banking/finance, domain-specific image analysis, neuroscience, low-level database optimizations). 8+ years professionally with Python and machine learning, and with Rust. Actively exploring remote opportunities where I can apply my combination of math and developer skills to interesting challenges.
Open to freelance/contract work (I can invoice via my own company) or full-time. Open to US work.
Re: Ask HN: Who wants to be hired? (November 2025)
#54---
- Technologies: LLM, AI-Agents, Python, PyTorch, TensorFlow, NumPy, pandas, scikit-learn, OpenCV, Hugging Face Transformers, FastAPI, Gradio, SQL, SQLite, PostgreSQL, MSSQL, REST APIs, Git, GitHub, Docker, Argo Workflows, Celery, RabbitMQ, Pinecone, OpenAI API, LangChain, Weaviate, RAG pipelines, CNNs, Transformers, MLOps, AutoML, XAI, MLflow, Streamlit, Flask, AWS, Jupyter, matplotlib, seaborn, pytest, shell scripting, CI/CD, Web scraping
---
- Résumé / CV: [Google Drive](https://drive.google.com/file/d/13-noXqbAhYvcUoqENXFSf_OZuMk...) | [LinkedIn](https://www.linkedin.com/in/mehmet-burak-sayici-a45294126/)
---
- Email: mburaksayici@gmail.com
---
- Highlights: - Built Gesund’s MLOps platform as first engineer; company later named to CB Insights AI 100 (2024) alongside OpenAI. - Managed $400k+ software contracts, represented Gesund in meetings with FDA & White House officials. - Co-authored a Stanford-affiliated AI paper during internship at Stanford Biomedical Data Science. - Currently lead the AI Interview App at Career.io (5,000+ MAU), integrating LLMs, vector search (Chroma), and agent-based feedback loops. - Built two LLM+RAG apps post-Gesund: VC due-diligence tool and YC-style growth tooling (built without LangChain). - Created MLOps system for energy forecasting across 8 cities (Python, PostgreSQL, weather APIs, LightGBM/XGBoost, MLflow). - Built a YouTube channel (15k+ subs) and a Udemy course on practical CNNs.
---
- Portfolio Links: - Stanford Biomedical Data Science Preprint: [arXiv](https://arxiv.org/abs/2002.04836v1) - AI Interview Simulation App (5k+ MAU): [Career.io](https://career.io/interview-prep) - Gesund.ai (First Engineer, 3 years, CB Insights AI 100 2024): [gesund.ai](https://gesund.ai) - Open Source XAI Library: [GitHub](https://github.com/mburaksayici/Why) - Blog on LLMs/MLOps: [mburaksayici.com/blog](https://mburaksayici.com/blog) - Udemy Course — Beyond MNIST Example: Practical Convolutional NNs: [Udemy](https://www.udemy.com/course/beyond-mnist-example-practical-...) - YouTube Channel (13k+ subs, 500k+ views): [MakineOgrenmesi](https://www.youtube.com/MakineOgrenmesi)
Re: Ask HN: Who wants to be hired? (November 2025)
#55Re: Ask HN: Who wants to be hired? (November 2025)
#56Location: London Remote: Hybrid Willing to relocate: No Technologies: React, Java, Python Résumé/CV: https://damonhayhurst.github.io/cv/ Email: damonhayhurst@gmail.com I'm a product engineer through and through, seeking greater ownership across both sides of the development lifecycle.
Re: Ask HN: Who wants to be hired? (November 2025)
#57[deleted]
Re: Ask HN: Who wants to be hired? (November 2025)
#58Re: Ask HN: Who wants to be hired? (November 2025)
#59Re: Ask HN: Who wants to be hired? (November 2025)
#60Remote: Yes
Willing to relocate: If needed
Technologies: Rails, Swift, Python (FastAPI), Scala, MySQL, MariaDB, AWS, Retool
Résumé/CV: https://drive.google.com/file/d/1sUNgSQwENIMkDMUXaZdXk2xLmJD...
Github: https://github.com/Perklone
LinkedIn: https://www.linkedin.com/in/rizky-maulana01/
Email: mrizky9601@gmail.com
I'm open to both part-time contract and full-time roles. At $WORK, I'm on the Developer Experience (DevEx) team, focusing on performance tuning for our core Rails application and building internal tools for other departments using Retool.
I'm comfortable working full-remote, I'm also a fast learner and eager to pick up new tech stacks as needed. I learned Rails on the job for this current role, which I actually found right here on HN!